| /external/tensorflow/tensorflow/contrib/distributions/python/kernel_tests/ |
| conditional_distribution_test.py | 50 def _sample_n(self, unused_shape, unused_seed, arg1, arg2): member in class:ConditionalDistributionTest._GetFakeDistribution._FakeDistribution
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| /external/tensorflow/tensorflow/contrib/distributions/python/ops/ |
| autoregressive.py | 208 def _sample_n(self, n, seed=None): member in class:Autoregressive
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| half_normal.py | 155 def _sample_n(self, n, seed=None): member in class:HalfNormal
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| conditional_transformed_distribution.py | 53 def _sample_n(self, n, seed=None, member in class:ConditionalTransformedDistribution
72 # We override `_call_sample_n` rather than `_sample_n` so we can ensure that
84 x = self._sample_n(n, seed, bijector_kwargs, distribution_kwargs)
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| cauchy.py | 178 def _sample_n(self, n, seed=None): member in class:Cauchy
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| geometric.py | 137 def _sample_n(self, n, seed=None): member in class:Geometric
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| gumbel.py | 183 def _sample_n(self, n, seed=None): member in class:_Gumbel
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| logistic.py | 178 def _sample_n(self, n, seed=None): member in class:Logistic
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| negative_binomial.py | 150 def _sample_n(self, n, seed=None): member in class:NegativeBinomial
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| onehot_categorical.py | 183 def _sample_n(self, n, seed=None): member in class:OneHotCategorical
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| poisson.py | 190 def _sample_n(self, n, seed=None): member in class:Poisson
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| deterministic.py | 167 def _sample_n(self, n, seed=None): # pylint: disable=unused-arg member in class:_BaseDeterministic
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| independent.py | 205 def _sample_n(self, n, seed): member in class:Independent
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| inverse_gamma.py | 195 def _sample_n(self, n, seed=None): member in class:InverseGamma
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| mixture_same_family.py | 246 def _sample_n(self, n, seed): member in class:MixtureSameFamily
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| relaxed_onehot_categorical.py | 248 def _sample_n(self, n, seed=None): member in class:ExpRelaxedOneHotCategorical
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| /external/tensorflow/tensorflow/python/ops/distributions/ |
| exponential.py | 129 def _sample_n(self, n, seed=None): member in class:Exponential
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| bernoulli.py | 125 def _sample_n(self, n, seed=None): member in class:Bernoulli
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| dirichlet_multinomial.py | 261 def _sample_n(self, n, seed=None): member in class:DirichletMultinomial
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| laplace.py | 158 def _sample_n(self, n, seed=None): member in class:Laplace
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| multinomial.py | 246 def _sample_n(self, n, seed=None): member in class:Multinomial
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| uniform.py | 170 def _sample_n(self, n, seed=None): member in class:Uniform
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| transformed_distribution.py | 384 def _sample_n(self, n, seed=None): member in class:TransformedDistribution
396 # We override `_call_sample_n` rather than `_sample_n` so we can ensure that
408 x = self._sample_n(n, seed, **kwargs)
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| /external/tensorflow/tensorflow/contrib/seq2seq/python/ops/ |
| helper.py | 84 def _sample_n(n): function in function:bernoulli_sample
90 return _call_sampler(_sample_n, sample_shape)
99 def _sample_n(n): function in function:categorical_sample
112 return _call_sampler(_sample_n, sample_shape)
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| sampler.py | 729 def _sample_n(n): function in function:bernoulli_sample
735 return _call_sampler(_sample_n, sample_shape)
744 def _sample_n(n): function in function:categorical_sample
758 return _call_sampler(_sample_n, sample_shape)
|
